M. Hoch, S. Gupta, J. Scheel, University of Rostock
Service center:
RNA Bioinformatics Center – RBC

“The Disease Maps Project is designed as a large-scale community effort. It is a network of groups that work together in order to better understand disease mechanisms. We exchange best practices, share information, develop tools to make it easier for all the involved groups to achieve their goals.”
During the COVID-19 pandemic, the Disease Maps Community (DMC) started the COVID-19 Disease Map project as “an open collaboration of many researchers and clinicians around the world. The goal is to develop as quickly as possible a description of host-pathogen interaction mechanisms specific to the SARS-CoV-2 virus to support the fast-track development of efficient treatments.” (https://disease-maps.org/)
We, from the SBI in Rostock, contributed to this project by manually curating submaps of viral interactions on human cellular pathways, such as the response to pathogen associated pattern or the respiratory chain complexes.
During the EuVsVirus hackathon (24th – 26th April 2020) we, together with other members of the DMC, participated as a team to effectively advance the creation of a COVID-19 disease map for data analysis and drug prediction. Many manually curated models and over 4000 relevant publication analyzed by text mining algorithms were combined to created effective Boolean models of the viral interactome that were analyzed to predict cellular responses to infection, potential drugs and drug targets.
In the end, we built up a seamless workflow based on well-established tools and platforms and produced a powerful computational hybrid to rationalize drug choice. The workflow will enable domain experts, such as clinicians, virologists, and immunologists, to collaborate with data scientists and computational biologists.

COVID-19 disease map website: https://covid.pages.uni.lu/map_curation
EuVsVirus submission: https://devpost.com/software/disease-maps-and-text-mining-for-drug-prediction